The security of computing resources and associated data is of high importance in many contexts. As an example, organizations often utilize networks of computing devices to provide a robust set of services to their users. Networks often span multiple geographic boundaries and often connect with other networks. An organization, for example, may support its operations using both internal networks of computing resources and computing resources managed by others. Computers of the organization, for instance, may communicate with computers of other organizations to access and/or provide data while using services of another organization. In many instances, organizations configure and operate remote networks using hardware managed by other organizations, thereby reducing infrastructure costs and achieving other advantages. With such configurations of computing resources, ensuring that access to the resources and the data they hold is secure can be challenging, especially as the size and complexity of such configurations grow.
Modern cryptographic algorithms provide high levels of data security. Current encryption methods, for example, can secure data such that unauthorized access to the data requires an impractical amount of time and/or resources. Such high-levels of protection, however, come at a cost. Generally speaking, higher levels of protection require higher levels of care and greater expenditure of computational resources. At the same time, not all transactions, however, require the highest available levels of security. As an example, data is often communicated from one computer to another using hypertext transfer protocol secure (HTTPS), even when the data is publicly available. Generally, a lot of computational resources is spent unnecessarily, resulting in higher latencies, higher energy usage, among other issues.